The eFlex Project-low

DEMAND
RESPONSE
The eFlex Project

eFlex TABLE OF CONTENTS
0 Executive Summary 5
01 Background 9
02 The eFlex Project 11
2.1 Targeting the Problem 11
2.2 Electricity Price and Flexibility 11
2.3 The Customers 13
2.4 Technical set-up 14
2.5 Support 15
2.6 PODIO; A Social Platform 15
2.7 Implementation 15
2.8 Regulatory Permission 15
03 Customer and Technology 17
3.1 Organisation 17
3.2 eFlex and the internal communication 18
3.3 Support 18
3.4 Technology handling from the Project perspective 20
04 Customer Behaviour Study 21
4.1 Method 21
4.2 Domestication of Technology 21
4.3 Moral Economy 22
4.4 Price as Control Signal 23
4.5 Feedback and Control 24
4.6 User Profiles 25
4.7 A Model for the Study of Flexibility 31
4.8 Communication 32
4.9 Conclusion on Behavioural Change 34
05 Measurements and analysis 35
5.1 Customer preferences 35
5.1.1 Method of calculation 35
5.1.2 Results 35
5.1.3 Conclusion – customer preferences 36
5.2 Flexibility, interruptibility and duty cycle for heat pumps 37
5.2.1 Data and data quality 37
5.2.2 Flexibility 38
5.2.3 Flexibility results 40
5.2.4 Conclusion – Flexibility 41
5.2.5 Interruptibility 41
5.2.6 Interruptibility results 41
5.2.7 Conclusion - Interruptibility 43

5.2.8 Duty Cycle 44
5.2.9 Duty cycle results 44
5.3 Grid impact based on load studies for three 10 kV feeders 45
5.3.1 Calculation set-up 46
5.3.2 Grid load shedding impact on NYM13 47
5.3.3 Grid load shedding impact on GLN16 47
5.3.4 Grid load shedding impact on HOL02 49
5.3.5 Load shedding through portfolio management control of heat pumps 49
5.3.6 Conclusion 51
5.4 Peaks having of residential customers load profile 52
5.4.1 Conclusion 54
5.5 Financial Benefits for the Customer 54
5.6 Conclusion 57
06 Lessons Learned and conclusion 59
6.1 Perspectives 61
07 Appendix A 63
7.1 Correlation Studies 63
7.2 Elspot price and grid tariff 64
7.2.1 Load and grid tariff 65
7.2.2 Load and overall price 66
7.2.3 Wind energy and overall price 67
7.2.4 Load and wind energy 68
7.2.5 Summary 70
eFlex
Published by:
DONG Energy Eldistribution A/S
Department of Grid Strategy
Teknikerbyen 25
2830 Virum
Phone +45 99 55 57 77
www.dongenergy.com
November 2012

5Executive Summary
EXECUTIVE SUMMARY
Flexible consumers are a corner stone in a smart energy system where resources are utilized
more efficiently – from the production assets, through the grid and to the customer. Realiz-
ing a smart energy system where flexible consumers adjust their energy consumption ac-
cording to the grid load, could improve the economics of introducing electric vehicles and
heat pumps. Through incentives (of some type) could a postponement of investments in new
grid capacity be achieve.
Understanding the dynamics of customers’ flexibility is essential for realising such a smart
energy system in which distribution companies can rely on flexibility.
To advance the understanding of consumer flexibility, DONG Energy Eldistribution A/S, the
distribution company under DONG Energy A/S, carried out the eFlex project during the
period from the summer of 2011 to the summer of 2012. The purpose of the project was to
investigating, what incentives could be applied to make private households participate in
load shedding in the distribution grid. The project included 119 households located in the
DONG Energy supply area in North Zealand and Copenhagen, Denmark. The majority of the
participating customers have heat pumps. Over time, the grid load that appears from the
many heat pumps is expected to increase the load toward the grid’s capacity limit. However,
heat pumps also bear a flexibility potential and could thus contribute to load shedding.
Technical setup
The customers volunteered for the project and were found partly through an advertising
campaign and partly through expression of interest in a public subsidy scheme for switching
from oil-fired burners to heat pumps.
The customers were provided with a home automation system with an integrated control
unit to interrupt the heat pump from operating during peak periods. The home automation
system in parallel offered the customers the opportunity to closely monitor the energy con-
sumption of various appliances in the house and in addition to control them by means of an
ordinary time scheme control. Furthermore, the customers were invited to share experiences
and get support on a social media, Podio. The aim with the latter two features was to raise
interest in energy consumption.
The heat pumps were interrupted according to a price control scheme. The price was a com-
bination of a spot market price, settled on North Pool day-a-head electricity market, a 3-step
grid tariff and the regular public service obligation and tax fees. The price control scheme
interrupted the heat pumps during price peak periods and released them to ordinary opera-
tion when prices decreased again. The control was made possible by a home automation
system with an integrated control unit. The system also gave the customers an opportunity
to monitor the consumption on other appliances and program these to switch on and off
according to a timer.
Drivers of flexible consumption
During the project period an anthropological study of user behaviour was carried out. The
project developed five different user profiles, each characterised by a set of (partly overlap-
ping) motivation drivers or incentives. These profiles showed, that although customers par-
ticipated in the project on equal terms, they did so with different motives.
The opportunity for achieving financial savings through being flexible was one incentive that
was investigated in the project. The project also showed that some customers engaged in
the project first and foremost due to their interest in new technology (e.g. the home automa-

6 Executive Summary
eFlex
tion system) and the opportunities this would provide. A simple personal drive for optimis-
ing resource consumption vis-a-vis avoiding a loss (irrespective of the lack of reasonable
balance between effort and savings) also showed to be an important incentive for many
participants along with the opportunities for learning. One of the most important incentives
showed out to be a concern for the climate change or environmental effects of energy con-
sumption. In such cases, customers perceived the price control scheme as a required feature
in the future energy system, in order to enable large amount of wind energy.
The report describes the five different user profiles in further details under the following
headlines:
• The Technician
• The Economist
• The Curious
• The Sympathetic
• The Comfortable
The user profiles show that even though the economy of a household attracts significant
interest, customers can not just be seen as homo economicus, i.e. narrowly self-interested,
rationally economic behaving individuals., The project has established a model for under-
standing the very complex social conditions determining flexibility potential in different
households.
From the project we have learned that whether talking about flexibility, user practice or cus-
tomers’ incentives for behavioural changes, the social conditions as well as the internal
culture in families have to be taken into account as an important part of the equation.
Still, the price signal may be the best single incentive to offer for automatic control of heat
pumps. Although we cannot consider the customers to be pure homo economicus, the price
signal is still easy to ascribe meaning to and most of the user profiles include financial sav-
ings as a partial driver for participating, albeit not necessarily as the most significant driver.
Developing other incentives could further encourage flexibility, but it is very difficult to de-
sign incentives useful for load shedding that address the concern for climate and environ-
mental impact of energy consumption or other more intricate interests that a customer may
have for participating in load shedding.
Technical project results
The project demonstrated that flexibility can be achieved in the private households without
perceptible loss of comfort. We cannot generalise the conclusion in quantitative terms as the
flexibility depends on a lot of factors e.g. the insulation of the house, outdoor temperature,
user behaviour, social conditions etc.
The heat pumps included in the project could be interrupted for up to 3 hours. Due to the
technical setup in the project, the majority of the heat pumps only remained interrupted for
about 1 hour in connection with very cold outdoor temperature. But the analysis leaves room
to believe that heat pumps could in many cases be interrupted for longer periods of time,
even under harsh weather conditions and thus can respond to more aggressive control
schemes without instigating household members to overrule the control by commanding
the release of the heat pump into normal operation.
The project revealed that the use of the so-called ‘party button’ (a function enabling users to
force start the heat pump) was limited to once every 3rd
month, indicating that the custom-
ers comfort was not seriously challenged during the project.
Simulating the impact on the grid from a larger number of heat pumps on one feeder (i.e. a
local stretch of the power grid), revealed a clear peak shaving effect. But compared to the

7Executive Summary
remaining load on the grid (generated by all other appliances), the question remains how
significant this achievement is?
We also discovered that the period during which the heat pumps could be interrupted in
general was too short compared to the average period of peak loads. Cascade control of the
heat pumps, whereby a portfolio of pumps are interrupted gradually, showed that the task of
shaving the entire load peak that arrive from private households can be solved by the flexible
use of heat pumps. This calls for careful consideration in relation to how distribution compa-
nies can instigate advanced interruption patterns, i.e. in cascades. As we will argue in this
report, a general variable grid tariffs may not be sufficient.
An important observation was made in relation to the expected thermal pattern when inter-
rupting and the later releasing the heat pumps into normal operation. When heat pumps are
released to normal operation after an interruption period, a so-called kick-back load (or cold
load pick-up) was expected to occur as the heat pump recovers the missing energy supply to
the house. However, the kick-back load was in many cases missing completely. The reason is
believed to be that of customer practice in the form of cooking or running other heating
generating appliances (especially wood stove furnaces) etc. Also solar radiation is likely to
have had a significant influence on the thermal performance of the home but the project did
not record such details.
Economic effect on the customer
The annual savings that the customers achieved by participating in the project range from
approximately DKK 250 (~35 €) to DKK 600 (~80 €) depending on whether the house is
well-insulated and the degree of interest of the household to participate in such programme.
This was obtained using price jump in the 3-step grid tariff of DKK 0.60 from peak price to
the next level. Another design of the grid tariff, e.g. including Saturdays and Sundays, could
increase savings but it would probably not be significantly higher than indicated above.
In addition to this, energy management practice provided by the home automation system
enabled 10% savings on average as regards the electricity consumption. It must be empha-
sized that this result was generated under such conditions and on the basis of a group of
customers with special interest in energy savings, that the result cannot be generalized. On
the basis of the eFlex project, it is not possible to conclude that energy savings at this level
can be achieved or maintained through the use of a home automation system or the like.
Future perspectives
On the basis of the eFlex project it can be concluded that heat pumps in private households
have a technical potential for delivering a significant reduction in the peak load that house-
holds incur on the distribution grid. To a large extent, customers are also willing to let their
heat pumps be controlled given that the appropriate incentives are applied.
This means that distribution companies could potentially base grid planning and operations
on this notion. But flexibility of heat pumps and similar appliances must be harnessed sys-
tematically by commercial actors in the energy market and the control scheme must be
executed using sophisticated algorithms that cut off and release a portfolio of heat pumps in
cascades. Using such methods, the value of heat pump flexibility will increase and can be
translated into reductions in the peak load of the distribution grid.
The project has uncovered various costumer motives for participating in a flexibility pro-
gram. Commercial actors may use this insight to design value propositions for flexible cus-
tomers. However for this to occur, variable tariffing of private household customers must be
enabled at a larger scale. In addition, as we will argue in this report, it may be necessary to
further develop the tariff concept and additional incentives offered by distribution compa-
nies. Only with such a development, will commercial actors have the required incentives for
controlling heat pumps through advanced algorithms. The possibility for applying variable

8 Executive Summary
eFlex
tariffs and other incentives on a larger national scale will also be critical for providing
the necessary potential for value creation through harnessing flexibility, i.e. a critical
volume of electricity consumption that might generate value through shifting load
from peak price to lower price periods.
Enabling variable tariffing of all flexible consumption, would spur all market actors –
commercial and regulated – to work towards establishing the basis for creating value
through harnessing flexibility. In connection to this, it is important to note that as the
eFlex project progressed, a new regulatory framework governing the electricity retail
market and relations to end-consumers, was passed by Danish legislators. As of Octo-
ber 2014 Danish distribution companies must address their grid tariffs to the retailer
rather than to the end-customer. The retailer will then present a single bill to the cus-
tomers they service. In the new regulatory setup, it will be the role of the retailer to
offer additional services and products such as home automation solutions directly to
the end-consumer. It will also be the role of the retailer and other commercial actors
to develop incentives that go beyond pure price. Fortunately, the results of the eFlex
project are applicable to the new regulatory context.

9Background
01 BACKGROUND
At the beginning of 2010, DONG Energy Distribution decided to launch the eFlex project. A
project that was designed to investigate private households’ participation in demand re-
sponse.
The major task of a distribution company is to secure electricity supply and distribution
companies in Denmark are concessionaire of the distribution grid in specific areas. They
enjoy monopoly. They also own the meters and handle meter data. Customers can freely
choose their energy supply from a range of electricity retailers, which is another business
and completely separated from the distribution company.
The background of the project is the decline in production of oil and gas in the North Sea
combined with the political intention of reducing CO2
emissions. This has inspired to look
around for alternative energy sources and preferably sources of Danish origin. As regards the
electricity sector, this is primarily wind energy as direct feed to the grid, while biomass sup-
ports the coal- and natural gas-fired power plants still in operation.
Wind turbines produce electricity according to the energy in the wind regime and this is of
course a production independent of the consumption pattern. The overseas connections to
Norway, Sweden and Germany together with adaptation at the power plants and some larger
local industrial facilities ensure balancing on the grid at transmission level.
However, research has revealed that domestic consumption of produced energy from wind
turbines is more profitable for Danish economy than to sell the power abroad. Therefore, the
Danish government has launched subsidy schemes for switching from worn-out natural gas
and oil furnace systems to heat pumps and for promoting electrical vehicles. The purpose is
to introduce more electrical appliances, i.e. a switch from the petrochemical (fossil) sector to
the electricity sector that can be supplied by renewable energy and at the same time, force
out fossil fuel from the transport and heating sector, eg. reduce CO2
emission.
For a distribution company the new appliances represent a specific problem. The grid is
designed to carry the maximum load, i.e. the cable dimensions depend on the maximum
load and not the amount of energy that it is supposed to transmit. If for instance, a large
number of electrical vehicles are used throughout the day and owners recharge the batteries
by the end of the day at the same time as the evening load peak (the so-called cooking
peak), the grid will require reinforcement in several places.
This is expensive and a postponement of the investment in grid reinforcement will bear a
considerable benefit. A postponement is made possible, if the maximum load can be dimin-
ished, i.e. load shedding. For example, charging the electrical vehicles at another time than
the most obvious and disrupting heat pump operation during normal load peak.
The purpose of the eFlex project was to investigate private households’ willingness to be
flexible in this respect.
To encourage customers to show such flexibility, the distributions companies’ contribution is
to enable wind energy in the energy system in a modern and cost-effective way.

11The eFlex Project
02 THE EFLEX PROJECT
Below is find a brief introduction to the idea behind and implementation of the eFlex project.
The chapter describes the equipment used and the interaction with the customers.
2.1 Targeting the Problem
In order to encourage load shedding in the consumer segment, price incentives become a
natural choice. However, studies have revealed that a relatively large segment of customers
is not sensitive to variations in electricity pricing, and other incentives may play a more
influential role in customers’ procurement behaviour. In general, customers’ procurement
behaviour is a reflection of their personal values, cultural ballast, experiences, and is usually
a mix of the above.
In addition, the potential range of variation in the electricity prices is relatively limited seen
from a distribution company’s point of view. In Denmark, tax and VAT of the electricity sup-
ply constitutes the largest part of the invoice to the customer (about 60%). The electricity
price and the transport price (contribution to the distribution company) are by and large of
similar size; 20% of the invoice each. Hence, achieving a behavioural change among cus-
tomers based on changes of the part of the price that the distribution company is responsi-
ble for is very limited.
Therefore, the basic philosophy of the eFlex project was to investigate what other incentives
could entail a behavioural change in the use of energy towards load shedding. In addition to
this, the project was to analyse the potential effect of load shedding by private customers on
the distribution grid.
To this end, two major tools were implemented.
Each customer was given a home automation system of the brand: Greenwave Reality. The
home automation system is essentially able to control electrical appliances’ on/off time and
measure each appliances’ energy consumption. Control of heat pump operation in terms of
interruption of the ordinary operation and time scheme for charging batteries of electrical
vehicles was integrated in the home automation system by means of sophisticated algo-
rithms.
On/off control of ordinary household appliances is not very interesting as regards load shed-
ding because the energy consumption of most ordinary household appliances is insignifi-
cant. Electrical under-floor heating would have been of interest to the project, as the poten-
tial for long time interruption is high, but only very few heating systems exist in Denmark
and the software for control was consequently not developed in the project.
The second tool consists of a social media platform that was established on basis of the
PODIO platform concept. The idea was to increase interest in energy consumption through
dialogue and inspiration. However, the content turned out to be different as described later
in this document.
The outcome of the project was analysed by two teams. An agreement was concluded with
the consultants Antropologerne.com to investigate customer behaviour in general, and a
technical team at DONG Energy Distribution was established to assess the effect of the
control of heat pumps and electrical vehicles on the distribution grid.
2.2 Electricity Price and Flexibility
Despite what has been said about customers’ insensitivity as regards price changes, the
customers were exposed to varying price signals. Even though some customers emphasise

12 The eFlex Project
eFlex
climate, environment or have a more sophisticated approach to prices than expected from
homo economicus, one or more signals will have to control interruptions of heat pumps and
charging of electrical vehicles, and here the price signal is useful, as it is easy to ascribe
meaning to the signal (no matter for what reason). This is not the same as concluding that
the price signal is the most reasonable signal and customers are only interested in savings.
As we will show later on, price is a very complicated concept and even though segments of
customers participate for a number of other (main) reasons than saving money, they still
may consider savings as attractive.
The customers of the project were charged an electricity price that consisted of two compo-
nents besides tax and VAT: an elspot1
market electricity price added to a 3-step grid tariff.
The 3-step grid tariff is shown in Figure 2.1. The aim was to expose the customers to two
versions of the varied grid tariff in order to detect a potential change in behaviour.
The elspot market is a day-ahead market; hence the price of every hour was predicable one
day-ahead. Customers had new meters installed that enabled hourly account statements.
Customers could choose between price signal for control of heat pump and charging of elec-
trical vehicle, a signal monitoring the amount of wind energy in the total energy mix in the
grid, and a balanced combination of the two.
Furthermore, customers could choose the balance between e.g. best price optimisation and
comfort, ie. the more a customer wishes to make financial savings, the longer time the heat
pump would be interrupted and the more negative effect on the level of comfort is to be
expected.
1 Elspot is the name of a day ahead market based spot price in the North Pool market (Nord Pool market)
6
0.576
DKK/kWh
Moderate variable grid tariff implemented
from october 1th 2011 to February 1th 2012
Standard flat tariff DKK 0.2720.276
0.176
8 12 17 19 21 24
6
0.876
DKK/kWh
High variable grid tariff implemented from
February 1th 2012 to July 1th 2012
Standard flat tariff DKK 0.2720.276
0.076
8 12 17 19 21 24
Figure 2.1 Variable grid tariff including the DKK 0.076 contribution to transmission company. The 3-step grid tariff is
only valid during weekdays. During weekends, the grid tariff is equal to the lowest step during the whole day.

13The eFlex Project
Finally, customers could set a minimum room temperature, so that the heat pump would
return to normal operation, in case the temperature in the room reached the minimum tem-
perature.
Based on the daily price pattern and the customers’ choices, control profiles were down-
loaded to each house for in-house control of the heat pump. If for any reason, a customer
wanted to override the daily control profiles, the home automation system was equipped
with a manual override; the so-called party bottom, that disregarded the control profile set-
tings for the remaining time of the 24-hour price forecast.
No matter what choices the customers made, they were invoiced the combined elspot mar-
ket price and the grid tariff. No safety net was provided for the customers to avoid even large
variations of the elspot market price which could result in unexpected high invoices, as this
could affect the behaviour and choices of the customers.
2.3 The Customers
119 customers participated in the eFlex project. 82 of these were heat pump owners and 28
customers fell in the category ‘ordinary’ households with no heat pump or electrical vehicle.
The 9 customers who owned electrical vehicles were too few and did not constitute a basis
for statistical analysis or safe assessment of general behavioural change.
The reason for the very few customers with electrical vehicles, who participated in this pro-
ject, was simply that no such customers were to be found in the DONG Energy supply area,
who also wanted to participate in the project.
All customers had to live in the DONG Energy supply area (customers of the Distribution
Company) but they could choose any electricity supplier (retailer) as long as they were billed
on the basis of a North Pool spot market price.
Customers were recruited through an advertising campaign in the DONG Energy newsletter,
through procurement of leads from a vendor of heat pumps and through a co-operation with
Energinet.dk’s project ‘From Windmills to Heat Pumps’. The latter recruited customers
through the public scrap schemes that supported the switch from worn out oil-fired burners
to heat pumps. DONG Energy co-operated with Energinet.dk as regards heat pump custom-
ers in the DONG Energy supply area.
Customers volunteered for the project and were, of course, interested in using the new
technology and the programme. Consequently, the customers were not representative of all
the customers living in the DONG Energy supply area but were positively bias toward the
project.
Almost all the customers lived in houses and only very few in apartments. The income level
was at the high end; almost 1/3 earned above DKK 900.000 and approximately 1/3 of the
customers had a high-level education.
25-39 years
40-59 years
21
54
19
2
60-69 years
70+ years
Figure 2.2 Age composition of the customers

14 The eFlex Project
eFlex
2.4 Technical set-up
After screening a large number of suppliers of home automation system, we chose Greenwave
Reality. We screened the companies for their ability to deliver according to Danish standards
and manage open data handling protocol like z-wave and Zigbee. At the same time, we wanted
the suppliers to show what other demonstration projects they have participated in. Furthermore,
we assessed their ability to co-operate, as we discovered that not all suppliers wanted to partici-
pate in a demonstration project and the brand as such, and the ‘history’ of the supplier could
affect the risk assessment of the project. Finally, we demanded to see a live demonstration of the
technology to ensure that the supplier in fact had a technology sufficiently developed to solve
the problems that we would encounter.
Greenwave Reality delivered standard two six-plugs power nodes and two single-plugs
power nodes to each household. In addition, the owners of heat pumps and electrical vehi-
cles were equipped with technology for measurement and control of these devices. A Gate-
way connected the home areas network by z-wave communication.
Besides measuring energy consumption of the heat pump and charging of the electrical
vehicle, the main electricity consumption of the household was measured. Measurement of
the electricity consumption used for invoicing purposes was however separated from meas-
urement of electricity consumption used in the eFlex for presentation to the customers in
order to avoid breakdown in or malfunctioning of the equipment resulting in faulty invoices.
Furthermore, customers were equipped with an iPod Touch for control of the devices or could
choose to do so in a more extended version installed in their home computer; a portal. The
GWR standard portal for home automation systems was further developed in co-operation
with DONG Energy’s IT department in order to incorporate control of heat pumps and elec-
trical vehicles. Many of portal screens were also developed based on a survey of the custom-
ers’ preferred manoeuvring and reporting screens, made by anthropologists of the Alexandra
Institute for DONG Energy.
Greenwave Reality supplied the communication from the gateway via the internet to the
server system including monitoring and execution signals and user portal. DONG Energy
supplied the back-end server system including database and algorithm for control of heat
pumps and electrical vehicles. The server system also collected elspot market prices, metro-
logical data etc.
Figure 2.3 A simplified illustration of the integration of IT and the Greenwave Reality supply.
DONG ENERGY IT
GWR server
Collect data
Read / write commands
Enable interface to backend
Backend server
Database
HP & EV algorithms
Collect external data:
Spotprize
Temperature
Secure
access
Interface
backend / GWR
USER UI BACKEND UI
GREENWAVE REALITY

15The eFlex Project
2.5 Support
DONG Energy provided first line support, and it was originally decided to offer this through the
Technical Hotline at DONG Energy which is open 24 hours a day.
2.6 PODIO; A Social Platform
In order to maintain communication with the customers, a Facebook-like platform was estab-
lished based on the PODIO concept. PODIO is developed for the purpose of co-operation and
can be shaped into many forms due to a flexible apps program.
All the customers were invited to join PODIO and 114 of the 119 customers did register as
users.
Besides being used for detailed explanations of various functions of heat pump control,
electricity prices etc., PODIO was used to extract perceptions and user practise from the
on-going debates and include these in the anthropological study of behaviour and change.
However, over time the main issues discussed in the PODIO universe were support ques-
tions rather than questions with a more future-oriented perspective.
2.7 Implementation
Greenwave Reality’s portal and control software were developed at the same time as the
development of server software in back-end. This process was initiated by an anthropologi-
cal study of user preferences via mock-ups of possible screen layouts.
The development of the software took almost a year. On 15 March 2011, the project was
launched but included only a few customers in order to remove the last software bugs. In
June 2011, owners of electrical vehicles were included in the system, and on 1 September the
remaining customers went online.
The project was closed on 1 July 2012.
2.8 Regulatory Permission
In Denmark, a project like eFlex cannot be launched without obtaining permission from the
energy authorities.
The project was subject to the following conditions:
• The customers should volunteer in the project and should be fully informed about the
conditions for participating and the date of termination
• The number of participants should be limited
• The project should contain a deadline for termination
• The participating customers should receive a meter for automatic remote reading.
• The variable grid tariff should be designed in such a way that DSO would receive no ad-
ditional revenue
• The results should be published
The eFlex project has met all these obligations - and this report meets the last condition.
Initially, the authorities were concerned that the project favoured only some customers (the
participating customers) which is against the regulation regarding discrimination. In order
to implement the eFlex project, a change in the law was required to enable implementation
of demonstration projects that included customers.

17Customer and Technology
03 CUSTOMER AND TECHNOLOGY
In this chapter is described the actions and organisation of DONG Energy’s resources for
running the eFlex project. The project organisation embraced a number of departments to
covers all operations and especially the organisation of customer support is considered.
3.1 Organisation
Besides the project manager, the project organisation consisted of three teams during the
implementation; Technology, IT and Customer Handling. When the project entered the op-
erational phase, the organisation was changed to other three teams; Technology & IT, Cus-
tomer Handling and Analysis. The team leader of the customer handling was the same per-
son throughout the project.
Below, the three teams the project were divided into several taskforces and required exten-
sive co-operation across DONG Energy.
At DONG Energy, the tasks were divided into the following departments:
* The process of changing subscription is complicated and contains a long notice period. The process depends on whether the customer had a subscrip-
tion with another supplier and wanted to change the subscription to DONG Energy, and whether they were DONG Energy supply obligated customers2
.
It was a prerequisite that all customers had a supply contract based on hourly readings and based on Nord Pool Sport market price.
** A contract governing the customers’ and DONG Energy’s responsibilities and obligations during the project.
*** During dismantling of the equipment after termination of the project, the Meter Department did not have the resources for such a special project at the
time and the task was assigned to the Customer Centre.
**** The customers were actually invoiced according to the spot market price and the variable grid tariffs, even though at the beginning, we did not know
whether the customer would save energy and money. We did not provide the customers with a safety net as this would exempt the customers from
‘real’ behavioural change. However, we rewarded the customer after end of the project.
2 Elspot is the name of a day ahead market based spot price in the North Pool market (Nord Pool market)
DEPARTMENT TASKS
Customer Centre Recruiting process
Questions related to invoices
Registration of change in power supply subscription*
Support related to questions regarding the contract**
Support related to customer’s social events
Billing Integration of the hourly measurement of energy in databases etc.
Registration of variable grid tariff for invoicing of customers
Submission of invoices
Meters Booking of electrician visit for installation***
Installation of eFlex equipment
Dismantling of eFlex equipment
Marketing Support to the content in information material etc.
Design of brochures
Submission of brochures etc.
Submission of contracts etc. and reminders
Registration of signed contracts
Digital Marketing Design and development of eFlex web site
Design of questionnaires and compiling of replies
Economy Submission of customer rewards after termination of project****
Legal Preparation of contract and conditions for participation in the project
Continued support regarding extension of contracts, letters etc.
Support for obtaining permission to execute eFlex (regulated by energy authorities)
Technical Hotline Technical support to customers.
Figure 3.1. Departments at DONG Energy in order to implement eFlex, and their tasks

18 Customer and Technology
eFlex
At first glance, the eFlex project may not be considered complicated in terms of the work
required by DONG Energy. However, especially the customer handling entailed a consider-
able amount of communication points in order to handle project enrolment, customers’
power supply subscriptions, installation of equipment, billing, legal issues, marketing, press
etc. and not least support.
3.2 eFlex and the internal communication
The internal communication and coordination to enrol customers and integrate them in the
project, as well as provide the technical support during operation, may be different for each
distribution company (or anybody who could consider making such a project). An important
overall learning experience with eFlex was that the resources required for these tasks can easily
be underestimated and may turn out to be a big surprise later in the process.
It is a prerequisite to have a team leader assigned to coordinate the communication and
document flow, and it should be considered which tools to implement in order to ensure that
nothing is left out.
3.3 Support
eFlex broke new ground with regards to the strategic direction towards demand response. By
taking customers in as partners in a project and offer them new technology in the form of intel-
ligent house equipment, required a lot of support.
The support comprised technical issues, billing, the project in itself etc. and had to be
planned and organised to avoid customers contacting random persons of the project team.
Initially, Technical Hotline was the first line of support. They could provide support round the
clock every day of the week. Technical Hotline’s normal task is to act as customers’ contact
point in connection with power failure in the distribution grid. We trained a taskforce con-
sisting of 14 persons in the use of eFlex equipment. Any questions and problems that they
could not handle were submitted to the Customer Centre (essentially questions to billing
and electricity prices) or specific persons of the Project Team. The latter could subsequently
submit questions to IT, Greenwave Reality etc.
A system was established to keep track of questions and problem solving. More general
answers and general information were announced on Podio.
Two significant observations were made. First, there were not enough questions and prob-
lems to maintain competences as regards all the technical details for all the staff members.
The frequency of questions that target each of the 14-person group was simply not high
enough for all to remain competent at the expected level. In addition, some staff members
were more motivated than others to accept this extraordinary and new work load which the
eFlex project entailed, and questions were soon directed to key persons and consequently
the remaining people in the group became less and less qualified in delivering support to
the eFlex project. Because the key staff was not always at hand, the amount of problems that
were transferred to the project team (second line support) increased.
Second, we also had to realise that customers prefer to communicate using different means,
and as regards the most active persons Podio soon became the preferred communication
2011 2012
MONTH MAR APR MAY JUN JUL AUG SEP OCT NOV DEC JAN FEB MAR
Phone
calls
158 64 31 41 71 91 91 63 41 30 32 19 27
E-mails 16 10 10 5 2 1 13 22 9 4 8 3 0
Figure 3.2 Number of contacts to Technical Hotline during the project period. The eFlex project involved 119 customers.

19Customer and Technology
channel for support. In PODIO, they could have a dialogue with highly qualified staff of the
project team and have their problems solved at the same time.
The use of Podio for support had the positive effect that if one person had a question to or
problems with the equipment, another customer could respond before the project team
members. Podio certainly had certainly a community building effect.
To some extent, the technology chosen was still in progress of development and rather new.
Therefore, we encountered some technical problems. The amount of inquiries to eFlex’s
general telephone number and common e-mail box appears from Figure 3.2. In addition,
quite a number of inquiries took place through Podio. The amount of inquiries could be
considered high but there was still insufficient basis for maintaining the necessary compe-
tences within the Technical Hotline.
Therefore, it was decided to direct the majority of support questions through Podio and
abandon the 24/7 support offered by Technical Hotline. Three persons within Technical Hot-
line were trained again and were closely involved in the project in order to maintain compe-
tences and interest. The fact that we no longer offered round-the-clock support caused no
problems.
By using a social platform like Podio as support, we strengthened the communication build-
ing effect. More persons would benefit from the solutions we provided and the increased
traffic on Podio offered a better basis for understanding the customers and their way of
thinking and increased the potential participants in discussions on Podio that we strived at.
An important observation was that even though the project team experienced a heavy traffic
on Podio regarding support, it was not all the customers that were familiar with the media.
As it appears from Figure 3.3, many customers still prefer phone calls to the use of Podio. In
this respect, the average age of the customers may influence the result (see Figure 2.3). Only
very few customers contributed active to Podio. The majority of customers limited them-
selves to reading the contribution of others.
Figure 3.3 Customers’ reply as regards use of and opinions on Podio
Social medias will be the future for support
I have read others contribution on Podio
I have made many contributions on Podio
Podio is a good tool for dialog
Good that Podio is a closed community
Respons time on Podio was satisfactory
Posio is a good tool for support
Max 100 0 10 20 30 40 50 60 70 80 90

20 Customer and Technology
eFlex
3.4 Technology handling from the Project perspective
eFlex was an innovation project. The technology was new and to a certain degree im-
mature and only limited experience from other projects indicated what to expect.
We conducted intensive surveys on potential suppliers, and DONG Energy IT depart-
ment developed software for control of heat pumps and charging of electrical vehicles,
which we initially tested in the laboratory and subsequently launched to a few custom-
ers. Customers were connected to the project step-by-step in order to allow us to learn
how to handle problems and learn down the route. We worked intensive on designing
the optimum support strategy and treated the customers with special events in order to
maintain their interest while at the same time, they experienced the problems of an
innovation project.
We faced a number of problems and the overall experience to avoid such problems in
future projects referred to improved communication and organisational cooperation.
Treating suppliers the same way as in a traditional role under a delivery contract causes
problems in relation to maintenance of hardware and software in innovation projects,
where major uncertainties and risks are handled. Too many issues are unknown and
what is more important; the learning curve during the project cycle is steep and many
changes have to be made during the process.
This can probably be handled by usual contract management, and so it was, but seen
in retrospect maintaining a tight project group with everybody participating would have
resulted in larger commitment and easier communication.

21Customer Behaviour Study
04 CUSTOMER BEHAVIOUR STUDY
Major achievement of the eFlex project arrived from a comprehensive anthropological survey
of customers behaviour and preferences. In the chapter below is described the methods
used, some theoretical reflections and the major results. In a separate report (in Danish) is
the survey results described more comprehensively.
4.1 Method
The difference between what a persons is thinking and what he does is a well-known dichot-
omy in social studies as well as in marketing studies. Several examples can be found to
illustrate that people are occasionally acting in opposition to what they believe to be their
values and priorities3
. Therefore, questionnaires are not always a fruitful method for social
research, no matter whether they are orally or in writing unless the questionnaire concerns
quantitative questions. In addition to this, questionnaires tend to reflect the questionnaire
designer’s mental model of the world and will not always match the model of the informant.
In the eFlex project, we concluded an agreement with the consultancy company Antropolo-
gerne.com to conduct a study of customer behaviour and what changes the home automa-
tion system entailed. The study was essentially conducted by home visits and cultural
probes (home exercises). In total, 48 home visits were included in the survey and each visit
lasted approximately 4-5 hours.
The study was conducted in three steps where observations and conclusions were gradually
elaborated through workshops with a larger analysis team that included DONG Energy key
staff.
4.2 Domestication of Technology
Customers are different in all aspects and not two customers can be said to have equal con-
ditions, wishes or values. Therefore, it is very difficult to generalise observations and conclu-
sions.
The Home Automation System from Greenwave Reality (GWR) was adopted in the houses at
different speed, difficulty and utility.
Initially, delivery of the equipment to a house may be considered from a more ‘mechanical
point of view’; simply equipment to be installed and used as intended. As Lucy Suchman4
showed in her study of use and troubleshooting in the handling of copy machines, the use
of technology is embedded in a conception of user practice in the head of the designer.
Machines’ interaction with the world and with people in particular, will be limited to the
intentions of designers and their ability to anticipate and limit the users’ actions.
However, the users can be very creative in the use of technology; from time to time in par-
ticular their misunderstood use of the technology represents the breach in the borders of
concept anticipated by the designers. ‘Creative’ use of technology is more a clash between
mental models than a clash between humans and the technology.
Akrich5
calls such inscription of the designers’ visions as scripts; the idea of the way users
were supposed to apply the design, but the idea is more or less the same as Suchman’s.
What this project clearly showed was that human actions were diversified and apparently
unpredictable, both in the use of the home automation equipment and in the practise within
consumption of energy.
3 The most distinctive advocates for this theory is Argyris and Schön but similar ideas of this dichotomy can be found with numerous other social scientists.
4 Suchman, Lucy A. Human-Machine Reconfigurations. Cambridge University Press 2007
5 Akrich, M. ’The Description of technical objects’ in W. Bijker and J. Law, Shaping Technology/Building society. Studies in Sociotechnical Change. 1992

22 Customer Behaviour Study
eFlex
The use of the equipment and the extent of its use depended very much on a negotiation in
the homes between the man, the wife and the children. Different interests and life priorities
became evident and the final instalment and use of the equipment were often a give-and-
take situation. It is a valuable experience and maybe the most important that we obtained
from the project that design and domestication of technology cannot ignore the internal
culture and identities made up by the family, and that there is no linear and straight forward
way to understand the domestication process. We cannot in any way limit our understanding
of domestication of technology to the functionality of the technology. There are human fac-
tors behind this and that makes all the difference.
As regards the domestication theories that rely on the Script approach and other actor-
network theories, it has the underlying assumption that supplying the customer with tech-
nology is a question of how he will use and incorporate the technology over time in his daily
life and practice. Knut H. Sørensen and Silverstone6
suggest that people and their socio-
technical relations may change as well.
This could be very well seen in the eFlex project and this was of course the very point. The
home automation system provided with great success an insight into the households’ en-
ergy consumption and habits. The general interest and probably also the complexity of the
energy prices resulted in customer knowledge of energy systems beyond what could be ex-
pected by the ordinary consumer.
This insight resulted in a change of habits that many other projects believed to have proven
impossible: change of habits based on information only. The difference to other project of
information based behaviour modification is probably that in eFlex it was not just informa-
tion but the system provided a learning of energy use. The insight and knowledge created an
interest and boosted internal competition (or play) as regards what was possible in terms of
saving energy. Use of dish washer and washing machines was for some made dependent on
the price forecast. Some customers also tried their best to change their habits in connection
with cooking and taking showers. However, we will never know whether the changed pattern
will last.
So people change too and therefore, domestication of technology has a wider implication
than just socialisation of technology (or as it is understood in the script approach): it is a
co-product of the social and the technical aspects - to use Knut H. Sørensen’s word. It is not
only obtaining of new technology in the homes via new practise, but people who have the
practise change too.
4.3 Moral Economy
Money as a mean for exchanging services and products is in all societies related to some
symbolic value. Parry and Block7
have proven the diversity in the perception of money for
exchange in several societies and households are no exemption. In Silverstone’s studies, he
found
6 Berker, Thomas (eds). Domestication of Media and Technology. Open University Press 2006.
7 Parry, J. and M. Bloch. Money and the Morality of Exchange. Cambridge University Press 1989
…it was also clear that in many families and households the
abstract value associated with money in the formal economy
would not need to be, and were not, upheld: the private economy
of help, reciprocity and nominal payments for services rendered,
did not depend on any models of rational value and fixed rates
of exchange.

Money and price are very complicated concepts when integrated in human practice. In the
project, there were many situations where customers’ perception of money was based on an
understanding deriving from internal cultures and identities within the borders of the family.
The concept of moral economy, which divides the conception of money into Household and
Home, appeared to be an immediate way to understand our observations and a promising
approach to discuss how technology makes sense to the customers.
Household and Home are two distinct set of mental models in use at the same time. The
household is the material and tangible life that has to do with exchange of values related to
the infrastructure framing the practice of the family. In many ways, it could be said that
household economy has to do with the basic needs of the household. It concerns the money
flow in and out of the house and energy savings etc. are usually discussed within this refer-
ence system.
Home refers to the construction of identity and the meaning ascribing to actions in view of
the family culture. It is a phenomenological term and reference system where money is used
for exchange in a way that does not appear rational in the formal economy.
The two reference systems coexisted side by side and were in the eFlex project expressed in
examples where customers on the one hand invested in energy savings and on the other
hand invested in energy consuming technology that supported their understanding of who
they were or referred to their interest sphere. Likewise, cases were found where energy sav-
ings spend on more energy consuming technology and investments in obvious non-benefi-
cial technologies although it was understood to be energy savings.
4.4 Price as Control Signal
When talking about load shedding, the most obvious solution appears to be to offer custom-
ers a variable price; a high price when the load is high and vice versa. Numerous projects
have tried this and eFlex too. It can be argued, considering the above observations about
moral economy and irrational economic behaviour, that price signal will not work as sole
incentive for flexible behaviour.
First and foremost, it is important to recognise the conclusion at which eFlex arrived: all
customers act based on a wide diversity of reasons and values. Some people will react eco-
nomical rational to a price change but it is probably not the majority.
Second, even though eFlex made some customers react based on information only, it is far
from sure that it would continue this way, if no further technical development took place that
could sustain the interest. In addition, this behaviour change would probably not include all
types of customers either. Anyway, it is widely recognised that information based behav-
ioural modification is an unreliable approach that is likely not to work in the long run. The
safe way to achieve a change in behaviour with regard to required load shedding is by pro-
viding some sort of technology that can apply the change according to a signal, ie. auto-
matically. It simply cannot be expected that customers continue monitoring a price signal
manually (or any other signal) and react accordingly; we need technology to do it for them.
It is an important observation that when the customers have accepted the technology that
automatically reacts correctly to a signal, it is like removing a ‘response practice’ from the
customers. A larger part of the customers will no longer pay attention to the control signal
as this is managed by the technology. Furthermore, whether the price signal is higher or
lower the reaction from heat pump interruptions and schedules for charging electrical vehi-
cles are the same. They are already scheduling demand response in the optimal way as they
simply react to achieve the maximum gain; e.g the price difference. Therefore, a distribution
company cannot expect to achieve more flexibility with higher price signal; the ‘behaviour’
will remain the same as this is ‘only’ control input to a technology and it is already acting
optimal according to the price.

eFlex
The customers are becoming insensitive to the price by using the technology.
When discussing prices and economy in relation to demand response, the discussion should
therefore be less focused on the design of the price signal than on the price of the technol-
ogy that will automatically offer load shedding. As soon as the customers have accepted to
purchase the technology, any signal would work, but for some, the promised financial benefit
of purchasing and installing the technology may be a decisive factor and in this respect is a
discussion of price signal design relevant.
Initially, we explained that the project assumed that the customers to be insensitive to price
variations. Nevertheless we did provide the customers with such a signal (and also an alter-
native ‘green’ signal), which appears to a contradiction in terms. As it will be shown later
customers act based on quite a number of reasons. However, the price signal is probably the
best to signify required load shedding as it is easy to ascribe meaning to for the customers
(whatever economic rationality can be buried in it) but as soon as they have accepted the
technology that actually provides load shedding, it could be any signal.
To put it bluntly, the consequence of this is that a distribution company cannot vary flexibil-
ity up and down by adjusting the price.
4.5 Feedback and Control
Before we return to more detailed findings, a few behavioural patterns more or less common
should be mentioned.
It is hardly something new that introducing consequences of actions in a visible in tangible
way will create a new response with whom who has taken the action. This is widely used in
energy management systems. Also in the eFlex project, the visualisation of the energy con-
sumption resulted in immediate changes.
What is more important as regards demand response is that the visualisation of energy use
also created a consciousness of electricity as an important commodity of life that unfolds in
the household. Most customers were expected to have a more or less superficial relation to
electricity use but the eFlex project, or rather the home automation equipment, no matter
that most of the equipment’s functionalities had no importance to load shedding, raised the
consciousness of energy use. This was considered as a prerequisite to promote interest in
the future intelligent energy system and load shedding.
Feedback on the consequences of action was the eminent functionality, and several sugges-
tions were discussed on PODIO as regards how to improve and expand the portal’s feedback
features. The importance of the feedback function in any system which intends to change
habits cannot be stressed enough.
Feedback also has another common feature. The home automation system including meas-
urement of consumption and control of heat pumps and electrical vehicle charging is a
probe into the private house, which most household naturally will react against. ‘My house is
my castle’ is not an all wrong way to put it for most customers, not least taken the preceding
discussion into account: the internal culture that families create for themselves.
Customers will inevitably see it as an intervention that ‘someone’ has taken control of various
appliances. Naturally, they are in favour of this taking place as they have agreed to participate
in the project but discussions on PODIO as well as observations in the homes indicate that
the feeling of safety and being in control of the events are important. This becomes clear from
the many suggestions of what should be available and visible on the portal and the more
tangible action of directly overruling the eFlex control system. Feedback from the system
concerning control actions and information in general as to what control is intended and why,
makes up for the lack of losing authority in own home and reinforces the feeling of safety.

In a number of cases, feedback has been experienced by customers in eFlex as insufficient
to offer the required feeling of safety – the safety that derives from knowing exactly what is
going on; and that raise requirements to the portal of being able to offer more understand-
ing and explanations.
The eFlex project identified a tendency towards a common interest in saving and optimising
the resources used by the family, although this is more or less outspoken depending on the
consumer segment that we are considering. Seen in a broader cultural context, the same
general tendency to preserve the status quo, that is well-known community/group charac-
teristics in anthropological research, can be found in the family culture: protection against
external threats, i.e. threats to the household economy, may result in a latent tacit reaction
to seek optimisation of the internal resources in the family.
Like any other cultural group, the family culture seeks to optimise the conditions and frame-
work that can provide as safe and comfortable life as possible. This may even be the case for
families who are inspired to give up part of the comfort zone in exchange for a larger course8
;
i.e. environmental issues.
Also for that reason, feedback is a key parameter. It offers the feeling that the probing into
the family culture and control of their appliances is not really an intervention (even though it
is) but that they do have control of the events and are supervising what is going on.
There can be no doubt that if we intend to modify habits within the safe walls of the family
home, feedback on the consequences of action and information about intentions, are the
single most important parameters to consider.
4.6 User Profiles
The eFlex project identified five different user profiles. Although the customers displayed an
impressive difference in behaviour and attitudes, it is possible to group them. However, the
groups will not represent strong distinctions in behaviour and attitudes. There is some over-
lapping and many customers will only point to belonging to only one specific group when
asked to choose only one.
In the following, we present the user profiles with short descriptions and in a ‘wheel’ with
nine characteristic drivers for participation in load shedding (and in the project in general).
Many more drivers could be found and many customers will probably think that it is not an
entirely correct description of their motivation drivers. However, the wheel is an attempt to
transfer the findings into a more sociological type of comparison and for further analysis. For
each profile, we have accentuated the most dominating motivation drivers and rated them
with stars.
The motivation drivers relate to the key customer in the family, who is the person that the
project usually communicated with and the person who has enrolled the household into the
project. There will be other motivation drivers present by the other family members and to
some extent the previously mentioned internal negotiation in the family culture on technol-
ogy domestication could be ‘mapped’ on the wheel.
Customers have been divided into the categories according to the findings from the anthro-
pological survey, and afterwards customers were asked which category described their moti-
vation drivers the best. The result was a very good match and the remaining customers were
subsequently asked also to choose a category that they felt suited their motivation the best.
‘The wheel’ is subdivided into three levels. The motivation drivers in the centre represent
focus on the household/home situations and how to improve the families’ immediate condi-
tions. The second level refers to drivers that have a dominating focus directed towards oth-
ers or the immediate surroundings. The third level refers to drivers that are directed towards
8 In a recent study undertaken by DONG Energy Distribution concerning the reason why customers invest in solar panels, the same behaviour patterns were
found. Some insisted on strictly financial reasons and others on strictly environmental/climatic reasons. However, for the latter group they would only give up
‘so much’ for the greater course and only to the extent, that it would not really threaten their household, and therefor only to the extent, that solar panel
investment made some financial sense. Not necessarily in a financially beneficial sense but the financial calculation could not be entirely out in the woods.

eFlex
Customer Behaviour Study26
Characteristics and
interests
Work and think in projects. A profound personality based on research. Interested in
mechanics/electronics and new technologies. Usually a front runner and willing to
test new ideas and technology.
Public spirit Examine the society development critically. Positive attitude to environmental pro-
tection.
Their relation to
electricity
Committed to questions about the energy sector
Motive for participat-
ing
Consider themselves to have a useful resource towards technology development
Practice in the eFlex
project
Focus on new technology and spend relatively much time and effort on examining
and controlling their energy consumption.
Typical educational
background
Typically an engineer or another technical education. Usually high-level education.
Typically employed in the industry sector.
Avoid waste and save money
Learn new things and personal development
Play and competition
Do something for others
Experiment with new technology
The feeling of doing the 'right' thing
Support environmental priority
Participate in technological development
Contribute to development in the society
MOTIVATION FOR PARTICIPATION
AND FLEXIBILITY
Individual
level
Social level
Society level
THE
TECHNICIAN

Characteristics and
interests
System thinking and control focus. Motivated by optimising and saving energy,
money and time.
Public spirit The most sensible action appeals to them.
Their relation to
electricity
Motivated by optimising and avoiding losses.
ing
Typically they have just acquired a new heat pump and consequently, the power
consumption has increased, and they want to be in control.
project
Typically use relatively more time at the beginning of the project to install and adjust
the technology in order to control appliance consumption and modify the house-
hold's behaviour in an optimum way.
Typical educational
background
Educational background within economics and vocational sector. Employed within
the information and communication sector.
AND FLEXIBILITY
Individual
level
Social level
Society level
THE
ECONOMIST

eFlex
the discussion of the society development in general.
Characteristics and
interests
A curious and investigating attitude to life and events. Motivated by learning new
things.
Public spirit Interested in society development in general
Their relation to
electricity
They mainly feel entertained by saving energy. It is a game or internal competition. It
is more a feeling of saving and not the real savings in household context, that is of
interest to them.
ing
A main driver is the potential learning that can be extracted from the project.
project
Experiment with the possibilities of learning where to save energy.
Typical educational
background
Have relatively more vocational training background compared to the other profiles.
High-level education is also strongly represented.
AND FLEXIBILITY
Individual
level
Social level
Society level
THE
CURIOUS

Characteristics and
interests
Idealists who want to do ‘the right thing’. They have time, motivation and a desire to
do something for others and for the environment.
Public spirit Engaged in society questions and problems.
Their relation to
electricity
Orientated towards the ‘green’ environment.
ing
For a ‘good cause’. It appears to be the right thing to do.
project
When they have made the optimum adjustment and found what behavioural change
is required, the GWR equipment is no longer of interest to them.
Typical educational
background
Many participants have a medium-length university education typically within human
science. Typically employed in the public sector.
AND FLEXIBILITY
Individual
level
Social level
Society level
THE
SYMPATHETIC

eFlex
Characteristics and
interests
Focus on comfort and convenience in everyday life. Concentrate on family and career.
Typically settled in high-tech luxury homes.
Public spirit Know about the society development.
Relationship to elec-
tricity
Electricity is convenient and should ‘just work’.
ing
Save money on the heat pump operation and do something for the environment.
project
After installation of the equipment they have not used much time on it. Typically,
only happy to leave control to DONG Energy.
Typical educational
background
High-level education is strongly represented. They are well-paid and typically manag-
ers or have their own business.
AND FLEXIBILITY
Individual
level
Social level
Society level
THE
COMFORTABLE

4.7 A Model for the Study of Flexibility
As mentioned earlier, an important finding in eFlex is the wide diversity of habits and mental
construct in the families. Technology is socialised into the internal family culture and the identi-
ties that unfold there, but it has wider implications than the considerations such as user genre
or script, as it affects the socio-technical relations too and creates new norms and habits.
The behaviour is very far from financially rational and the term moral economy has been
used to emphasise the importance of non-financial features in actions.
One of the major achievements of the behavioural studies in eFlex was the creation of mod-
els enabling us to understand the complexity and categorise the features in the jungle of
diversified habits. The models help us to design communication strategies in future actions
towards smart grid and design value proposition tailor-made to specific segments.
It is important to stress that the model represents some limitations. In the smart grid sense,
the Distribution company’s interest is represented by flexibility, interruptions, load shedding,
investment planning, while the customers’ sphere evolve around change of energy use, sav-
ings, avoiding losses, financial benefit, environmental concern and responsibility. To link
such differences into one model is not easy.
The model somehow transfers the findings of the project from the social and cultural discus-
sion to enable a sociological survey. During the eFlex project, it has unfortunately not been
possible to take it all the way to quantification of the group characteristics.
Of the four groups in Figure 3.1 that represent the way we have categorised some character-
istics, Willingness is the group that is the easiest to affect through offers and communica-
tion. The group consists of
Willingness:
• Interests, attitudes and values
• Relation and attitude towards technology, economy, climate and environment
• Indoor climate and comfort habits.
Change of willingness to participate in load shedding depends very much on how the family
ascribe meaning to their flexibility. It has to make sense on the set of values they priorities
according to customer segments.
Family composition
• Men, women – age
• Children
• Pets
Single persons or couples living alone are more inclined to be flexible than families with
Figure 4.1 A model as starting point. We consider the customers to have various potentials for flexibility and the
question is what kind of technical and financial propositions can be offered together with communication strategies
and relations to the customers that can transform such potential to real flexibility.
Willingness
Family composition
Life Situation
Thermal characteristics
of the house
POTENTIAL FLEXIBILITY
Communication
and relations
Technical and financial
concepts, products
and services

eFlex
children and pets (as a matter of fact, the observations indicate that pets have an effect on
the willingness to be flexible).
Life Situation
• High energy consumption and bill
• Change of larger appliances in the family
• Renovation, expansion and/or moving to new residences
• Life phase – i.e. soon to be retired
Certain conditions can be a motivation for flexibility. This is typically if changes are already
taking place and tacit habits become visible or due to known burning platform in form of
high energy bills etc. Changing life phase may change the attitude towards flexibility too.
People to be retired soon may be motivated to reduce living expenses or seniors for whom
career is less interesting and children have moved out of house have more time to be focus
on new technologies and society problems.
Thermal Characteristics of the house
• Insulation
• Heating technology
• Control devices
The house in itself is of course a basic condition for flexibility. Light houses with poor insula-
tion can only have its heating system disrupted for a short while and vice versa. Similarly, a
heating system suitable for interruption should of course be available.
4.8 Communication
Traditionally, the distribution company communicates with the customers primarily via the
invoice that the customers normally receive each quarter. For an ordinary Danish customer
the invoice is difficult to understand due to the detailed breakdown of the bill. It is expected
that only few customers study the invoice critically.
The only other time that an ordinary household customer meets the distribution company is
when power supply is down or when the customers have questions to the bill. It is no sur-
prise that the ordinary household customer’s relation to the use of electricity is superficial.
eFlex opened and experimented with several alternative communications. The Home Auto-
mation portal (and parallel facilities on the provided iPod Touch) offered a direct insight into
the online consumption of energy and divided the consumption into details on the con-
sumption of the appliances that was connected. Compared to normal household customers,
the eFlex customers’ motivation to visit and use the portal was animated by the fact that
they had more opportunities to examine the use of energy and the consequences of their
actions.
Besides the portal, the customers were supplied with a social platform based on Podio, and
of course also the opportunity to use e-mail and the phone.
In Figure 4.2 the different user segments requirements and attitude towards the various
opportunities for communication is described.

COMMUNICATIONANDTHEUSERPROFILES
THETECHNICIANTHEECONOMISTTHECURIOUSTHESYMPATHETICTHECOMFORTABLE
GWRPortalEmphasisonthepossibilitiesof
theportal.Dailyuse.
Emphasisonthepossibilitiesof
theportal.Dailyuse.Mainlyuse
theportalandtoasmallerextent
alltheotherGWRequipment.
Emphasisonlearning,playand
competitiveoptions.
Notusesineverydaylife.From
timetotimeitisreviewedbut
nevergointodetails
Notusedineverydaylife.Appreci-
ategraphicrepresentationsand
theappstoiPodTouch/iPhone.
PodioExchangeofexperimentsand
professionalquestions.Participat-
ing.
Calculationofafinancialnatureis
sharedwithotherusers.
Mainlyreadbutdon’tcontributeas
Podioisconsideredaverytechni-
calforum.
SeePodioasinsuperableanddo
notuseit.Readthenewse-mails
thatsumupactivitiesonPodio.
Useaslittletimeaspossibleon
theprojectandconsiderPodioas
time-consuming.
InvoiceInvoiceisusedasacontroltool
andisimportant.
Importanttooltocontroldevelop-
ment
Appreciatethegraphicpresenta-
tionsandcomparisons.
PriortotheeFlexparticipation
theyneverpaidmuchattentionto
theinvoice.
Justpaythebill.Thevaryingprices
havehowevergeneratedsome
interestintheappliances’con-
sumption.
Telephoneand
e-mailsupport
Demandingcustomerforthe
supportteam.Requirethatsupport
teamhaveprofoundexpertise.
Primarilyfuture-oriented.Make
proposalsforpotentialchanges.
Cross-checkownunderstanding.
Onlysupportonerrors.Havingdifficultywithtechnical
issuesandrequestassistanceby
phone.
Expectservices.ExpectDONG
Energytocontactthemifthereare
problemsorerrors.
FuturewishesSimplycannotreceiveenough
feedbackandexpectthedistribu-
tioncompanytobeanadvanced
dialoguepartner
RequestfeedbackinDKKand
especiallythepossibilityforcom-
parison.Appreciate‘theliving
invoice’.
Feedbackwithcompetition.Prob-
ablyinterestedinmoregeneral
informationtolearnfrom.
Instructionsbyvideo.Sumup
newse-mailswithlinktorequired
actionorinformation.Summaries
onconsumption.
Facilitiesthatcouldgatherthe
familywouldincreaseinterest.
Expectclearandsimpleinforma-
tiononconsumption.
Figure4.2Communicationandtheuserprofiles.

eFlex
4.9 Conclusion on Behavioural Change
The problem in drawing conclusion is that more experiments were conducted at the same time
and a possible change in behaviour can only with difficulty be ascribed to single interventions.
However, the following can be concluded with some certainty:
• A very serious mistake can be made if customers are considered one uniform mass. The
eFlex project very clearly demonstrated that customers can be divided into segments and
these segments are motivated by different combinations of value propositions, and commu-
nication has to be made on different media and concern different issues. The studies have
shown that households build internal family cultures themselves depending on culturally
inherited habits of the individuals and the multi-faceted social situation. A simple and eas-
ily understandable model cannot be presented but to some extent, customers can be subdi-
vided into the segments with more or less the same values, perception and priorities.
• Price signal (varying electricity prices) is an extremely complex concept to use as behav-
ioural moderator. Customers who we have asked directly will answer that price is impor-
tant and they expect ‘something’ in return for flexibility. However, they are motivated by
more issues to actually change behaviour and show flexibility. First, customers do not
make purely rational financial decisions. Second, the value of electricity may have differ-
ent meaning and priority depending on the social reference system in which it is dis-
cussed. Third, an automatic control system to provide the flexibility is required, as it can-
not be expected that a customer continuously change consumption patterns ( by manu-
ally adjustment of electrical appliances) depending on a price signal (or whatever signal
is used). The consequence being that higher or lower price will not result in more or less
flexibility. The savings which a varying price signal entails is only interesting when dis-
cussing the cost for the automatic control system.
• Not surprisingly, the home automation system and/or the close feedback on energy con-
sumption and the consequences on the electricity bill, increased interest in energy ques-
tions and fuelled flexibility. The customers in eFlex volunteered for the project and were
positively biased towards providing the flexibility. However, the conclusion of the impact of
the home automation system is drawn from the interest apparently emerging from ‘play-
ing’ with the opportunities that the system provided.
There is hardly any doubt that participation in the project and/or focus on energy consump-
tion that the equipment provided, have a positive influence on the customers’ attitude. What
we found a bit surprising was that the majority of customers had a very clear prior under-
standing of the fact that flexible consumption would be required in future.
In this regard, the learning from eFlex is hardly surprising: when you manage to direct cus-
tomers’ attention to an issue, the interest in what lies ‘behind’ this issue will increase.
All customers should be invoiced on
basis of variable tariff
I beliveve that all in the future need
to have a flexible consump.
eFlex have change my attitude
to flexibility positively
I will in the future use home auto.
to control and monitoring
eFlex gave me a good understanding
of variable tariffs
I prefer monthly bills to quarterly
Monthly bills contributed to
my focus on consumption
0 10 20 30 40 50 60 70 80 90 100
Figure 4.3. Customers’ attitude to flexible energy consumption after participation in the eFlex project. A maximum of
100 possible points.

05 MEASUREMENTS AND ANALYSIS
This chapter presents the measurement data and results.
The heat pump customers can choose their preferred heat pump control strategy:
• Wind : Optimisation9
based on wind power generation
• Price: Optimisation by price signals (sum of elspot market price and grid tariff used in
eFlex)
• Price + Wind : Optimisation by combination of the two mentioned above
In general, two thirds of the customers chose a control strategy according to price, and nearly
the rest of the customers chose price+wind. The detailed analysis is presented in the following
section.
Since the customers have chosen both price+wind and in particular price control strategies,
a correlation study of wind generation and price forecasts with respect to consumption fore-
casts has been performed and is presented in Appendix A. In general, the study conclude that
there is a correlation between price and grid load, hence a price signal can in the general
picture be used for controlling heat pump interruption. In order to determine a link between
wind production and grid load there is a need to develop a more sophisticated signal than
wind generation forecasts.
In the following sections are presented customer preferences concerning their control strate-
gies, data and analyses of optimisation measurements and flexibility, and impact on grid
load. The final section presents a study of the financial gain for the customers for participa-
tion in the heat pump optimisation.
5.1 Customer preferences
This analysis aims to illustrate customer preferences and the behavior related to a range of
adjustment options:
• The choice of optimization control ie: a) price signal, b) signal reflecting the wind energy
mix of the total energy in the grid or c) a balanced combination of the two.
• Adjusted minimum room temperature. Customers could adjust a minimum room tempera-
ture prompting the heat pump to re-start (overriding the chosen optimization control
period).
• ‘Party button’. In case customers want exception from the optimisation, they can activate
the so-called party button, which ignores the control profile for 24 hours.
5.1.1 Method of calculation
Whenever a change was made in the configuration at the customer, a new line was entered
in the database – this meant that the same configuration could occur more than once a day.
Theoretically this could cause the same configuration to be counted more than once. It was
decided to interpolate available data so that only one optimisation was obtained per day per
customer.
Subsequently, the number of customers who selected a specified type of optimisation and
used the party button was counted.
5.1.2 Results
It is complicated to present a continuous monitoring of the parameters as the customers
actually adjust the parameters. Instead, we hereby present three snapshots to demonstrate
the preferences.
9 Interruption of a heat pump is not a simple process. In order to achieve financial gain (a maximum wind energy content for that matter) cautions have to be
taken to avoid the heat pump starts up again during the price peak. The question is then: when to start interruption? The time of starting the interruption
depends on the house thermal isolation and the outdoor temperature (of which the later changes over time). We have tried to develop an algorithm that
produce the maximum financial benefit (or wind energy utilisation) and therefor from time to time use the term optimisation for interruption.

36 Executive Summary
eFlex
Figures 5.1 below illustrate observed customer preferences recorded specific days in Decem-
ber 2011, January 2012 and February 2012. The customers’ choice of configuration has been
examined around year-end where the heat demands are usually high. It has also been de-
cided to include February 2012 because on 1 February 2012, the grid tariff was increased
from 0.60 DKK/kWh to 0.80 DKK/kWh during peak hours.
Explanation of glossary terms:
• Wind Optimisation based on wind power generation
• Price Optimisation by price signals (sum of elspot market price and grid
tariff)
• Wind + Price Optimisation by combination of the two mentioned above
• No opt. Optimisation not selected
• Override Party button used
From figure 5.1 it is seen that some of the customers change the settings of type of optimi-
sation over time. The reason could be the change in outdoor temperature, which decreased
significantly during January. Another reason could be that the wind+price optimisation part
resulted in no logical control of the heat pumps depending on the wind regime. The custom-
ers may have had a more environmental friendly approach but as we have shown in Appen-
dix A, use of wind energy as optimisation parameter is complicated seen from the custom-
er’s as well as the distribution utility’s point of view . However, it is still interesting that
about one third of the customers emphasise the importance of the environment, which rein-
force the results of the behavioural analyses that customers cannot be seen in the light only
of homo economicus.
The manual override (also called the party bottom) was in use by approximately 1% of the
119 customers at all time (or at least during the three days used in this example). This cor-
responds to each customer using the party bottom once every 3 months on average.
The minimum room temperature remained for the majority of customers at the default tem-
perature set upon delivery of the equipment, 170
C. In addition to the rare use of the ‘party
button’, we can conclude that the customers’ comfort zone has not been seriously chal-
lenged.
5.1.3 Conclusion – customer preferences
All heat pump customers that participated in the project enabled the heat pump optimisation
control. Approximately two thirds of the heat pump customers chose to control their heat pumps
with respect to price signals, the rest of the customers chose a signal with a mix of wind produc-
tion and price. From December to February approximately 20% of the customers changed their
preference control scheme from wind+price to price.
Figure 5.1 Costumer preferences recorded as snapshots in the period December 2011 to February 2012.
DECEMBER
2011
JANUARY
2012
FEBRUARY
2012
TYPE OF CONTROL
Wind 3% 4% 2%
Price 53% 68% 74%
Wind + price 44% 27% 25%
No opt. 0 0 0
OPTIMIZATION
ENABLED
Yes 100% 100% 100%
No 0 0 0
OVERRIDE
Yes 1% 1% 1%
No 99% 99% 99%

37Measurements and analysis
The customers have rarely used the override function, which cancels optimisations in a pe-
riod of 24 hours, and have rarely changed minimum indoor comfort temperature. This im-
plies that the optimizations have not challenged the customers comfort significantly.
5.2 Flexibility, interruptibility and duty cycle for heat pumps
This section presents the heat pump measurements results. The effect of the optimisation is
below described in two methods
• Flexibility: How much energy can be removed from the actual hour with respect to the
estimated consumed energy without optimisation?
• Interruptibility: For how long a period can the heat pump be turned off during an optimi-
sation period?
The heat pump duty cycle is defined as the ratio between the actual hourly consumption and
the installed power. In the following sections we use measurements of the duty cycle from all
heat pumps (with and without optimisation).
The grid is challenged mostly in the winter season due to high consumption profiles and
heating. Since the grid is dimensioned on basis of the maximum possible load we focus on
data from the winter period. Thus, in the following sections results are presented from data
obtained in the winter period 2011-11-01 to 2012-02-21.
5.2.1 Data and data quality
Results from the below studies are based on water-water heat pumps. It has been decided
not to mix the results from different heat pump technologies mainly due to large differences
in thermal efficiency (COP-factor) which may lead to misinterpretation of results.
The input parameters for the above analyses are:
• Power consumption, calculated as kWh/h from the data processing.
• Optimising routine (price, wind, mix).
• Outside temperature forecast (from weather forecast portal).
• Total rated power of the customer heat pumps. Technical data sheets for all the heat
pumps have been provided from each heat pump manufacturer containing data of the
installed power and consequently the maximum power consumption.
Figure 5.2. Ideal load operational profile and variable grid tariff to explain flexibility.
0
1
2
3
4
5
6
7
8
9
0
10
20
30
40
50
60
70
80
90
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
H.Ppowerconsumption[kW]
Winterhightariff[øre/kWh]ex.VAT
Hour
Heat pump - flexible operation and grid tariff
starh hin,m hstop,m hstart,e hin,e hstop,e
Plow
Phigh

38 Measurements and analysis
eFlex
Some data has been neglected due to data errors and poor network coverage in the custom-
ers’ homes which caused periods where data could not be collected.
5.2.2 Flexibility
In general, the term ‘Flexibility’ is the result of moving the electricity consumption of a cus-
tomer from periods with high demands to periods with less demands.
Figure 5.2 above shows an example of an operational profile of a heat pump in the period
with variable network tariff. (The red curve illustrates a winter period with high tariff during
peak period).
The high tariff starts at 8:00. However, the heat pump does not necessarily stop immediately
when reaching the high tariff. This is due to the fact that the optimising routine seeks to
avoid that the immersion heater needs to be switched on during the optimising period in
case sufficient heat has not been accumulated inside the house. Switching on the immer-
sion heater causes the power consumption to increase significantly to Phigh
until the electri-
cal immersion heater is switched off when reaching hstop,m
and the pump is running at normal
load, Plow
determined by the compressor unit and circulation pumps. The phenomena of
excess power consumption is denoted “Kick-back” in the figure10
. This is not an ideal situa-
tion and furthermore, the kick-back situation may coincide with a period where the grid tariff
is high and the utility grid is heavily loaded. In a worst case scenario where the “Kick-back”
phenomena occurs on many heat pumps, this may cause critical situations with risk of over-
loading the power grid. It must be mentioned that due to variation in outside temperature
and tolerances on optimising parameters, there is no guarantee that “Kick-back” will always
appear outside periods of high grid tariffs. In figure 5.2, examples are shown with “Kick-
back” appearing before the end of a high tariff period during the morning and “Kick-back”
appearing after the end of a high tariff period during the evening.
For calculation of the flexibility the challenge is to estimate how much energy the heat pump
would consume in case it was not optimised. During the hours where the heat pumps are
optimised (turned off), the average electricity consumption (kWh) is calculated based on an
estimate of the average electricity consumption during the last three hours prior to initiating
the optimising routine. This is a reasonable estimate according to the duty cycle measure-
ments we present in Sec. 5.2.9.
Comparing the estimated and actual consumption, it is possible to quantify the customer’s
flexibility and thus the amount of peak shaving (moving of electricity consumption outside
the intervals of peak load).
Flexibility is defined during the morning (8.00-12.00) and evening (17.00-19.00) according
to the below formulas. These time intervals are chosen because of the time intervals defined
in the 3-step grid tariffs.
This definition of flexibility is only in the view of the distribution company’s interest, ie. re-
garding the peak loads in the grid. Other types of flexibility could be interesting, eg. trading
on the balance market.
10 In other literature also known as cold load pick-up
Flex, morning (%) =
Estimated kWh, morning - actual kWh, morning
Estimated kWh, morning
100
Flex, evening(%) =
Estimated kWh, evening- actual kWh, evening
Estimated kWh, evening
100

39Measurements and analysis
In figure 5.2, the term Flex (%) is determined by the size of the ‘area’ which can be moved
outside the optimising periods compared with the actual area remaining inside the optimis-
ing periods. Defining the term “peak shaved energy” as the difference between estimated
and actual consumption, the flexibility can be calculated as the ratio of shaved energy com-
pared to estimated energy. In other words, the mathematical definition of flexibility used
here is the relative amount of energy we can remove from the period where load shedding is
wanted. Using this definition, flexibility not only depends on the specific set of conditions for
a house but also of the time. It is evident, that a household’s flexibility is not the same dur-
ing morning and evening and may vary during a year.
For instance, if estimated heat consumption is 16 kWh during the morning and the con-
sumption was only 4 kWh during the optimising period, 12 kWh has been removed from the
optimising period and Flex,morning = 75%.
It should be noticed that flexibility is defined according to the grid tariff’s high price signal
(see Figure 2.1). Only energy removed from inside the time period of the grid tariff’s high
price period is considered in the flexibility calculation. That is, if the maximum price occurs
at 22 o’clock due to the interfering of the spot price and heat pumps are interrupted with the
purpose to avoid energy use at that time, it is not considered in the flexibility calculation.
Similarly if “Kick-back” occurs outside the optimizing window, this will not contribute nega-
tively to the estimated flexibility. In the optimizing calculation routine, the above has been
taken into account.
FLEXIBILITY RESULTS DURING 17.00-20.00
Temperature range 15 5 -5
5 -5 -15
No. of optimisations 561 1300 200
Estimated 17.00-18.00 298.29 1060.18 157.76 kWh
Estimated 18.00-19.00 351.40 1483.68 259.87 kWh
Estimated 19.00-20.00 72.57 78.82 0.00 kWh
Estimated sum 722.26 2622.69 417.63 kWh
Actual 17.00-18.00 142.87 421.37 82.89 kWh
Actual 18.00-19.00 151.35 612.50 125.28 kWh
Actual 19.00-20.00 38.35 31.10 0.00 kWh
Actual sum 332.57 1064.97 208.17 kWh
Shaved 17.00-18.00 155.42 638.82 74.87 kWh
Shaved 18.00-19.00 200.05 871.18 134.59 kWh
Shaved 19.00-20.00 34.22 47.72 0.00 kWh
Shaved sum 389.69 1557.72 209.46 kWh
Flex 17.00-18.00 52% 60% 47%
Flex 18.00-19.00 57% 59% 52%
Flex 19.00-20.00 47% 61% N/A
Figure 5.3. Flexibility results during 17.00-20.00. The estimated energy consumption during the optimization period
is calculated on basis of the energy consumption 3 hours before interruption. The flexibility is calculated as the rela-
tive amount of energy that can be removed from the period we intent to interrupt.

40 Measurements and analysis
eFlex
5.2.3 Flexibility results
Figure 5.3 shows the results of the flexibility study between 17.00 and 20.00. The results are
shown for 3 various ranges of outdoor temperatures, ie range 5 - 15°C, -5 - 5°C and -15 -
-5°C. All energy estimates and measurements are calculated in kWh.
The table in Figure 5.3 lists the no. of optimisations for each temperature range. It is seen
that the lowest temperature range has a significant smaller number of optimisations com-
pared to the other temperature intervals. However, since the lowest temperature range rep-
resents a worst-case for both flexibility values and household consumption profiles, we focus
on these results.
It appears that the relative flexibility in the period 17:00 to 18:00 and 18:00 to 19:00 is more
or less the same. Thus, if the heat pumps are optimized in a period of 1 hour the exact hour
of optimisation is not important, since we obtain the approximate same flexibility whether
we optimise between 17:00-18:00 or 18:00-19:00.
The flexibility of these heat pumps is approximately 50% for one hour. This means that we
can reduce the consumption from the heat pumps by 50% when performing a one hour opti-
misation.
Figure 5.4. Flexibility results during 8.00-12.00.The flexibility is calculated as the relative amount of energy that can
be removed from the period we intent to interrupt. The estimated energy consumption during that period is calculated
on basis of the energy consumption 3 hours before interruption.
FLEXIBILITY RESULTS DURING 8.00-12.00
Temperature range 15 5 -5
5 -5 -15
No. of optimisations 227 779 100
Estimated 8.00-9.00 73.19 79.23 198.73 kWh
Estimated 9.00-10.00 66.24 786.10 83.62 kWh
Estimated 10.00-11.00 52.28 960.31 4.09 kWh
Estimated 11.00-12.00 73.34 827.52 6.32 kWh
Estimated sum 265.05 2653.16 292.76
Actual 8.00-9.00 21.28 29.39 94.57 kWh
Actual 9.00-10.00 26.11 297.84 35.46 kWh
Actual 10.00-11.00 20.39 357.76 2.82 kWh
Actual 11.00-12.00 27.31 310.31 6.07 kWh
Actual sum 95.08 995.30 138.91 kWh
Shaved 8.00-9.00 51.92 49.84 104.16 kWh
Shaved 9.00-10.00 40.13 488.26 48.16 kWh
Shaved 10.00-11.00 31.89 602.55 1.27 kWh
Shaved 11.00-12.00 46.03 517.21 0.26 kWh
Shaved sum 169.97 1657.86 153.85 kWh
Flex 8.00-9.00 71% 63% 52%
Flex 9.00-10.00 61% 62% 58%
Flex 10.00-11.00 61% 63% 31%
Flex 11.00-12.00 63% 63% 4%

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